Our Obsession with Quantity is Costing Us Quality
Neil Krikul
Marketing Consultant | ?? Wasteless Marketing | Sustainability Leader (CISL) | Podcast Host | Guest Lecturer
Numbers have always played a significant role in defining one’s value.
Hiring managers usually look at the number of years of experience that a candidate has.
Job applicants would explain their effort by the number of applications they submitted, rather than the quality of the applications.
Workers usually get paid by the number of hours, whether you’re an employee or a freelancer, while the rate may vary based on the value you can prove of yourself.?
And a value of a thing is indicated by its price.
But number is only a representation of its value, which may or may not be valid, and can easily be misrepresented and manipulated.
Yet, we tend to place more value on quantitative data (numerical information) than qualitative data (descriptive information), because the former is objective, and can be measured and standardised, while the latter is more subjective and requires more critical thinking.
Both have a role to play in problem-solving, proving a hypothesis and human advancement. Qualitative data gives us insights, while quantitative helps verify how representative it is to predict future outcomes.?
Nonetheless, unless you work in research, most people will deal more with quantitative data or numbers, especially in daily financial transactions.
There’s no doubt that numbers or ‘data’ in general has become a goldmine for businesses in the highly digital-driven world, helping us make better decisions by looking at historical data to make predictions, which can now be fed to Artificial Intelligence.
But have we got to the point where we have shifted too far in relying on quantitative data that we lose touch with qualitative data? When it’s the latter that delivers the quality and is not just a representation of it.
There are three consequences that I have seen from this overemphasis on quantity that we’re losing our quality:
There are many contexts in which this is panning out, but from my observation as a Marketer, I see this scenario happening in three areas: among people, promotion and product.
Quantitative data is making us more risk-averse
Risk-averse People
As mentioned, years of experience usually is an indication of how qualified a candidate is for the role. But even with more years, it doesn’t mean that the candidate knows how to do a job well or effectively, it just means that they’ve been doing it longer.
While it may be a reliable indicator of the candidate’s capabilities, as the number of years does come with valuable experience, that’s what everyone would think.
As all the data and information are now available everywhere, people have written books and content to share their years of experience and failures, which the readers can learn in an instant. While it may not be as memorable as the actual experience, it still gives them something to look out for and avoid costly mistakes.
One thing that the hiring manager doesn’t ask because it’s not a compulsory part of qualifying a candidate is how much learning the candidate has put in outside work.
Hence, ten years of experience from Candidate A may or may not equal five years of experience from Candidate B who also spent extra time learning outside work.
So by focusing too much on the quantity: years of experience, companies and hiring managers may miss out on highly capable candidates that could make more impact.
In addition, when looking at a candidate’s tenure, companies may reject those who jump around a lot in shorter tenure. After all, it’s costly to hire and train someone up. So why hire them if they aren’t likely to stick around for long? It’s more secure to hire an okay talent who will stick around.
But as prof Mark Ritson said:
“Sometimes longer tenure simply enables marketers to become even more useless for even longer.”
Candidates who change jobs around usually are the ones who are driven to achieve more, and there are always reasons why they move on, especially when they are driven to grow and not given the opportunity to.
So again, by focusing on the number, hiring managers may feel like they get more value out of less driven candidates who will stick around for longer but will miss out on candidates who are driven to make more impact and grow while bringing the company along with them.?
Nonetheless, it may just come down to whether who is the right fit rather than who is qualified.
Risk-averse Promotion
In the advertising effectiveness principles, there’s a concept of Share of Voice which indicates the share of brand awareness among the category. It is also referred to the amount of media spend by the brand. And due to its relationship with the Share of Market, brands need to maintain its spend in order to maintain or achieve their desired market share.
In an increasingly crowded platform, organic content is not enough anymore. Marketers need to pay to reach their buyers and reinforce brand associations to maintain their mental availability.
So working out a budget for paid advertising can bring about success. But it’s not the only path.
The other ones are hard to track and quantify because they’re about quality. It’s the creatives or ads that get used.
Each creative would deliver different outcomes, as the research has shown, creative has the highest percentage of sales contribution by advertising element, at 47%.
Yet most brands would invest more in ad spend than crafting engaging ads that people talk about. They prefer to spend big on a mediocre ad because developing an ad involves running past stakeholders, who can be risk-averse and may find it hard to support something that is not quantifiable, creativity.
As a result, more than 50% of ads are ignored while brands waste billions in ad spend yearly.
Risk-averse Product
Historical data helps inform us what worked and what didn’t work in the past, and while it cannot predict the future 100%, it does provide a safe zone to be in to minimise the chance of failing.
As everyone stops trying new things and sticking with what we already know, with publicly available data, they tend to end up with the same set of information, therefore, ending up with the same results.
The film and entertainment industry is also a good and obvious example of this. How many reboots, prequels and sequels have we seen in the past two decades? If it worked before, it must work again, and it will if the execution is good.
Consequently, we’re missing movies that are original, that have never been done before and are nothing like it. Who’s going to be the new generation of writers following JK Rowling or George R.R. Martin? Or are we just going to keep milking existing franchises as much as possible?
It might be more challenging in the modern age, ironically with more tools available, for writers to come up with original ideas - which could be a topic of another blog post. While the production company probably prefer doing something that guarantees movies and return on investment, unlike in the past when we didn’t know how it was going to perform until it was released.
In fact, Faris Yakob mentioned in his WARC article that:
"If creative work was deterministically predictable then movie studios would only release hits. It cannot work that way... In modern marketing, signals and statistics are both abundant and immediate and suggest that marketing outcomes are predictable - this is a deeply flawed idea."
Have we reached the end of the line of novel ideas and trying new things?
Quantitative data is making us more wasteful
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Wasteful People
Since the industrial revolution, amount of hours has always been a measure of work’s input. But as Cal Newport suggested in his new book Slow Productivity, we’re in a different time now.
Paying knowledge workers by hours is not the best way to go about it. What one can achieve in an hour will vary between individuals.
Some companies prefer to have employees in the office so they can physically see that they’re working, productively or unproductively, and count the number of hours they’re in there, when on the contrary, they could produce a better quality of work with less time when they work remotely without distractions or the boss looking over their shoulders.?
Because for knowledge workers, it’s more difficult to measure the quality of work, it’s much easier to just start the clock.
So even if the knowledge workers get the job done faster and correctly, they’re still required to be in the office, it’s almost counterproductive. Why bother finishing the project early if you still need to be in the office? Why bother taking on more projects if we’re getting paid by hours, not the amount of projects completed? Why bother becoming more productive and efficient if the system doesn't reward us for doing so?
Even if we’re incentivised to take on more projects, it still relies on quantitative data (amount of projects completed), which could come at the cost of quality or staff burnout.
Clearly, we should find a way to improve the system before it all goes downhill.
Wasteful Promotion
As mentioned previously, brands waste billions in advertising that doesn’t work, with more than 50% of ads getting ignored or failing to make customers feel something, therefore impacting their effectiveness in driving the bottom line.
It’s easier to blast the boring message to build meaningless impressions than to invest in crafting engaging and memorable ads that deliver meaningful impressions.
In addition, a globally renowned digital marketer Neil Patel recently shared a tip on how much a LinkedIn account should post for optimal growth, which includes.. are you ready?
3 to 5 videos a week, 1 to 4 Images a week, 4 to 5 Carousels a month, 4 to 5 Lives a month, 1 to 2 Polls a month, one Article per month and 4-17 Comments a day.
Imagine a platform where everyone follows this guide. From the creator's perspective, would more content mean less quality from your content? Most likely. From the consumer perspective, in a crowded platform, it’s the quality that will stand out, not quantity.
It’s the meaningful impression that counts.
Wasteful Product
When it comes to product, volume is always emphasised. If we sell more, we grow more, even at the cost of the planet.
Fast fashion, which contributes to 10% of global carbon dioxide emissions, is a great example of this where customers are advertised new and cheap clothing that they may wear a few times and throw them away once the new trend comes in.
Quality in fashion refers to many things such as durability, comfort, versatility and style. But because fast fashion clothing is not often used for long, quality is often ignored, which ends up in a huge amount of waste and landfill.
Companies and manufacturers focus more on volume rather than craftsmanship because machines can produce more at lower costs without human touch or creativity, those that create meaningful value for things. Why bother knitting a special sweater to give away as a gift when you can order from Temu cheaper and faster?
Quantitative data limits our magic
Humans love to rationalise things because we fear the unexplainable. It triggers our survival mechanism. We do so by grouping and predicting based on historical data.
Unmagical People
Imagine ways that we categorise people, by race, gender, age, occupation, nationality, star signs and personality. There tend to be some common behaviours that are expected of a certain trait, based on previous records or numbers. But by categorising people, we limit both their and our potential by putting them in a box.
When we first meet someone of a certain group, our confirmation bias will kick in as soon as they perform a behaviour that aligns with our view, when one action certainly doesn’t define a character. Just because someone chooses to stay in one night doesn’t mean that they’re an introvert.
Secondly, it also works at the personal level. When you are told that you belong to a certain group that tends to behave in a particular way, you tend to conform based on that stereotype.
However, human personality and traits are more fluid than that, as they can also be affected by context and other factors. For instance, when you identify yourself as an introvert, you tend to act to fit into that stereotype by not approaching people or making any eye contact, when you could be, if you were in the right environment.
There’s a funny saying that humans invented logic and reasons to win an argument. I don’t think it’s entirely true, as they also help us communicate and pass on ideas. However, it still serves as a reminder not to take logic too seriously. They’re only there as a guide and evidence and don’t always represent facts or reality.?
As soon as we realise that, we can start to go outside the box and unlock our limitless potential.
Unmagical Promotion
Brands and agencies are taking Marketing and advertising measurement more seriously like ever before, as the industry tries to prove its value. Businesses need to find out their return on investment.
Brands and pre and post-test their ads to ensure maximum effectiveness. There are best practices that they can follow, depending on the objectives.?
While this is great news, it does make us more risk-averse as mentioned previously, and with less risk, there will be less triumph that could have come from companies taking risks and experimenting with uncertainty.?
When we look back to advertising effectiveness in the mid-to-late 2000s, brands still manage to be more effective than now even without the modern tools, as seen in the IPA study with Peter Field below.
The study blamed the rise of short-term performance marketing, in which brands can track their numbers - return on ad spend - instantly. This has become shaky since the removal of cookies as a response to rising customer privacy concerns.?
While modern brands are given tools and frameworks to follow for greater effectiveness, they need to be aware and not let those put them in a box and find a way to experiment with creativity.
The problem with following best practices is that it moves you closer to others who share the same framework. Yet, no one can guarantee how to produce something viral, it comes from consistent experimentation and the willingness to fail.
Unmagical Product
The good thing about a data-driven product is that you can get it personalised just for you. Imagine a personalised TV program, meal plan and grocery list. Happy customers, happy business.
But the world's greatest innovations such as cars, iPhones, Electric Vehicles, Facebook or Airbnb never came from historical quantitative data and predictions, they came from qualitative insights, which involve understanding customers underlying needs.
"It is much easier to be fired for being illogical than it is for being unimaginative. The fatal issue is that logic always gets you to exactly the same place as your competitors." - Rory Sutherland
Questions to ask to discover a better quality
No doubt that quantitative data still plays a significant role in our decision-making. But we need to first question the quality of things before we begin counting.?
People
Promotion
Product
Lastly, can we not let numbers limit our potential?